Conference contribution
(Original article)


Predictive Load Management in Smart Grid Environments


Publication Details
Author(s): Mutschler C, Löffler C, Witt N, Edelhäußer T, Philippsen M
Publication year: 2014
Conference Proceedings Title: Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems (DEBS'14)
Pages range: 282-287
ISBN: 978-1-4503-2737-4

Event details
Event: 8th ACM International Conference on Distributed Event-Based Systems (DEBS'14)
Event location: Mumbai, India
Start date of the event: 26/05/2014
End date of the event: 29/05/2014
Language: English

Abstract

The DEBS 2014 Grand Challenge targets the monitoring and prediction of energy loads of smart plugs installed in private households. This paper presents details of our middleware solution and efficient median calculation, shows how we address data quality issues, and provides insights into our enhanced prediction based on hidden Markov models.

The evaluation on the smart grid data set shows that we process up to 244k input events per second with an average detection latency of only 13.3ms, and that our system efficiently scales across nodes to increase throughput. Our prediction model significantly outperforms the median-based prediction as it deviates much less from the real load values, and as it consumes considerably less memory.



Focus Area of Individual Faculties


How to cite
APA: Mutschler, C., Löffler, C., Witt, N., Edelhäußer, T., & Philippsen, M. (2014). Predictive Load Management in Smart Grid Environments. In Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems (DEBS'14) (pp. 282-287).

MLA: Mutschler, Christopher, et al. "Predictive Load Management in Smart Grid Environments." Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems (DEBS'14), Mumbai, India 2014. 282-287.

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